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Cuda parallel test add mark large #4723
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Merged
oleksandr-pavlyk
merged 3 commits into
NVIDIA:main
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oleksandr-pavlyk:cuda-parallel-test-add-mark-large
May 19, 2025
Merged
Cuda parallel test add mark large #4723
oleksandr-pavlyk
merged 3 commits into
NVIDIA:main
from
oleksandr-pavlyk:cuda-parallel-test-add-mark-large
May 19, 2025
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pytest.mark.large is intended to mark test making large GPU memory allocations.
shwina
approved these changes
May 16, 2025
🟩 CI finished in 1h 15m: Pass: 100%/187 | Total: 1d 07h | Avg: 10m 14s | Max: 38m 35s | Hits: 97%/282436
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CUDA Experimental | |
stdpar | |
+/- | python |
CCCL C Parallel Library | |
Catch2Helper |
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+/- | CCCL Infrastructure |
+/- | libcu++ |
+/- | CUB |
+/- | Thrust |
+/- | CUDA Experimental |
+/- | stdpar |
+/- | python |
+/- | CCCL C Parallel Library |
+/- | Catch2Helper |
🏃 Runner counts (total jobs: 187)
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129 | linux-amd64-cpu16 |
15 | windows-amd64-cpu16 |
12 | linux-arm64-cpu16 |
12 | linux-amd64-gpu-rtxa6000-latest-1 |
11 | linux-amd64-gpu-rtx2080-latest-1 |
5 | linux-amd64-gpu-h100-latest-1 |
3 | linux-amd64-gpu-rtx4090-latest-1 |
leofang
approved these changes
May 16, 2025
alliepiper
approved these changes
May 19, 2025
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Description
closes #4722
This PR introduces
pytest.mark.large
tocuda.parallel
test suite and marks tests allocating over2**20
elements as large. CI script running project's test use-m "not large"
.Verified that this helps by running
CUDA_VISIBLE_DEVICES=1 pytest -s -n 6 -m "not large" tests
locally, where device 1 is RTX A400 4GB consumer GPU card.Of course, with a 64-core machine,
CUDA_VISIBLE_DEVICES=1 pytest -s -n auto -m "not large" tests
runs into out-of-memory issues.Checklist